CN116080326A - Control method and system for semi-active suspension - Google Patents

Control method and system for semi-active suspension Download PDF

Info

Publication number
CN116080326A
CN116080326A CN202310079638.8A CN202310079638A CN116080326A CN 116080326 A CN116080326 A CN 116080326A CN 202310079638 A CN202310079638 A CN 202310079638A CN 116080326 A CN116080326 A CN 116080326A
Authority
CN
China
Prior art keywords
fuzzy
semi
active suspension
suspension
road surface
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202310079638.8A
Other languages
Chinese (zh)
Other versions
CN116080326B (en
Inventor
张博强
赵浩翰
李宗瑾
孙朋
张勋
冯天培
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Henan University of Technology
Original Assignee
Henan University of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Henan University of Technology filed Critical Henan University of Technology
Priority to CN202310079638.8A priority Critical patent/CN116080326B/en
Publication of CN116080326A publication Critical patent/CN116080326A/en
Application granted granted Critical
Publication of CN116080326B publication Critical patent/CN116080326B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G17/00Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
    • B60G17/015Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G17/00Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
    • B60G17/015Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
    • B60G17/018Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by the use of a specific signal treatment or control method
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60GVEHICLE SUSPENSION ARRANGEMENTS
    • B60G17/00Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
    • B60G17/06Characteristics of dampers, e.g. mechanical dampers
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation

Landscapes

  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Vehicle Body Suspensions (AREA)

Abstract

The application discloses a control method and a system of a semi-active suspension, comprising the following steps: determining an external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model; acquiring random disturbance information of a road surface and performance parameters of a semi-active suspension; determining a fuzzy regulation strategy according to the performance parameters of the semi-active suspension and the random disturbance information of the road surface; according to the fuzzy regulation strategy, the regulated control parameters are determined, and the suspension dynamic deflection, the wheel dynamic load and the vehicle body acceleration are regulated according to the regulated control parameters, so that the peak values of the suspension dynamic deflection, the vehicle body acceleration and the vehicle body dynamic load can be effectively reduced.

Description

半主动悬架的控制方法及系统Control method and system of semi-active suspension

技术领域Technical Field

本申请属于控制系统技术领域,尤其涉及一种半主动悬架的控制方法及系统。The present application belongs to the technical field of control systems, and in particular, relates to a control method and system for a semi-active suspension.

背景技术Background Art

悬架作为现代汽车重要组成部分,对乘坐舒适性和行驶安全性有着重要的影响。传统被动悬架系统无须外部能量输入,结构简单,因而获得广泛应用,但它只能在悬架工作时消耗能量,其阻尼特性不能随路面激励变化。主动悬架能获得一个优质的隔振系统,实现理想悬架的控制目标,但能耗大,成本高,结构复杂。而半主动悬架是无源控制,作动器价格低、能耗小、结构简单,且其控制品质接近主动悬架。As an important part of modern automobiles, suspension has a significant impact on ride comfort and driving safety. Traditional passive suspension systems do not require external energy input and have a simple structure, so they are widely used. However, they can only consume energy when the suspension is working, and their damping characteristics cannot change with road excitation. Active suspension can obtain a high-quality vibration isolation system and achieve the control goal of an ideal suspension, but it consumes a lot of energy, has high cost, and a complex structure. Semi-active suspension is passive control, with low actuator price, low energy consumption, simple structure, and its control quality is close to that of active suspension.

近些年,以模糊控制和PID控制为基础的控制技术迅速发展。将不同的控制方式结合起来,采用各自的优点,可以获得更好的优化效果。如增量式算法与PID控制器结合,改善了半主动悬架系统的性能,提高了工程车辆的行驶平顺性和操作稳定性。采用粒子群优化算法整定PID滑模控制器(SMC-PID)的参数,改善了控制器的效果,提高了磁流变减振器的性能。In recent years, control technologies based on fuzzy control and PID control have developed rapidly. Combining different control methods and taking advantage of their respective advantages can achieve better optimization results. For example, the combination of incremental algorithms and PID controllers improves the performance of semi-active suspension systems and improves the ride smoothness and operational stability of engineering vehicles. The particle swarm optimization algorithm is used to adjust the parameters of the PID sliding mode controller (SMC-PID), which improves the effect of the controller and the performance of the magnetorheological shock absorber.

目前,在研究悬架系统算法时,通常将减振器简化为弹簧模型而忽略其外特性,这就使得在半主动悬架算法的计算和实际过程中存在误差,也使得该悬架系统算法的普及受到限制。At present, when studying the suspension system algorithm, the shock absorber is usually simplified into a spring model and its external characteristics are ignored. This leads to errors in the calculation and actual process of the semi-active suspension algorithm, and also limits the popularization of the suspension system algorithm.

发明内容Summary of the invention

本申请意在提供一种半主动悬架的控制方法及系统,以解决现有技术中存在的不足,本申请要解决的技术问题通过以下技术方案来实现。The present application intends to provide a control method and system for a semi-active suspension to solve the deficiencies in the prior art. The technical problem to be solved by the present application is achieved through the following technical solutions.

第一个方面,本申请实施例提供一种半主动悬架的控制方法,所述方法包括:In a first aspect, an embodiment of the present application provides a control method for a semi-active suspension, the method comprising:

根据预先建立的变阻尼减振器仿真模型,确定减振器的外特性曲线;According to the pre-established simulation model of the variable damping shock absorber, the external characteristic curve of the shock absorber is determined;

获取路面随机扰动信息和半主动悬架的性能参数;Obtaining random disturbance information of the road surface and performance parameters of the semi-active suspension;

根据所述半主动悬架的性能参数和所述路面随机扰动信息,确定模糊调节策略;Determining a fuzzy adjustment strategy according to the performance parameters of the semi-active suspension and the random disturbance information of the road surface;

根据所述模糊调节策略,确定调节后的控制参数,并根据所述调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节。According to the fuzzy adjustment strategy, the adjusted control parameters are determined, and according to the adjusted control parameters, the suspension dynamic deflection, the wheel dynamic load and the vehicle body acceleration are adjusted.

可选地,所述预先建立的变阻尼减振器仿真模型的输入为不同的输入电流和激励速度,输出为所述外特性曲线。Optionally, the input of the pre-established variable damping shock absorber simulation model is different input currents and excitation speeds, and the output is the external characteristic curve.

可选地,所述路面随机扰动信息为路面不平度系数的标识。Optionally, the road surface random disturbance information is an identifier of a road surface roughness coefficient.

可选地,所述预先建立的模糊调节策略包括通过输入变量偏差和输入变量偏差变化率,确定对应的变论域的伸缩因子。Optionally, the pre-established fuzzy adjustment strategy includes determining a corresponding scaling factor of the variable universe through an input variable deviation and a rate of change of the input variable deviation.

可选地,所述输入变量偏差和输入变量偏差变化率包括五个第一模糊集,所述第一模糊集分别表示不同的模糊状态,所述第一模糊集包括PB为正大、PM为正中、PS为正小、ZE为零、NS为负小、NM为负中、NB为负大;所述变论域的伸缩因子包括五个第二模糊集,所述第二模糊集表示对电磁阀开闭控制趋势,所述第二模糊集包括ZE为闭、S为小、M为中、B为大、K为开。Optionally, the input variable deviation and the input variable deviation change rate include five first fuzzy sets, and the first fuzzy sets respectively represent different fuzzy states, including PB for positive large, PM for positive medium, PS for positive small, ZE for zero, NS for negative small, NM for negative medium, and NB for negative large; the expansion factor of the variable domain includes five second fuzzy sets, and the second fuzzy sets represent the control trend of the opening and closing of the solenoid valve, and the second fuzzy sets include ZE for closed, S for small, M for medium, B for large, and K for open.

第二个方面,本申请实施例提供一种半主动悬架的控制系统,所述系统包括:In a second aspect, an embodiment of the present application provides a control system for a semi-active suspension, the system comprising:

第一确定模块,用于根据预先建立的变阻尼减振器仿真模型,确定减振器的外特性曲线;A first determination module is used to determine the external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model;

获取模块,用于获取路面随机扰动信息和半主动悬架的性能参数;An acquisition module, used to obtain road surface random disturbance information and performance parameters of the semi-active suspension;

第二确定模块,用于根据所述半主动悬架的性能参数和所述路面随机扰动信息,确定模糊调节策略;A second determination module is used to determine a fuzzy adjustment strategy according to the performance parameters of the semi-active suspension and the road surface random disturbance information;

调节模块,用于根据所述模糊调节策略,确定调节后的控制参数,并根据所述调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节。The adjustment module is used to determine the adjusted control parameters according to the fuzzy adjustment strategy, and adjust the suspension dynamic deflection, wheel dynamic load and vehicle body acceleration according to the adjusted control parameters.

可选地,所述预先建立的变阻尼减振器仿真模型的输入为不同的输入电流和激励速度,输出为所述外特性曲线。Optionally, the input of the pre-established variable damping shock absorber simulation model is different input currents and excitation speeds, and the output is the external characteristic curve.

可选地,所述路面随机扰动信息为路面不平度系数的标识。Optionally, the road surface random disturbance information is an identifier of a road surface roughness coefficient.

可选地,所述预先建立的模糊调节策略包括通过输入变量偏差和输入变量偏差变化率,确定对应的变论域的伸缩因子。Optionally, the pre-established fuzzy adjustment strategy includes determining a corresponding scaling factor of the variable universe through an input variable deviation and a rate of change of the input variable deviation.

可选地,所述输入变量偏差和输入变量偏差变化率包括五个第一模糊集,所述第一模糊集分别表示不同的模糊状态,所述第一模糊集包括PB为正大、PM为正中、PS为正小、ZE为零、NS为负小、NM为负中、NB为负大;所述变论域的伸缩因子包括五个第二模糊集,所述第二模糊集表示对电磁阀开闭控制趋势,所述第二模糊集包括ZE为闭、S为小、M为中、B为大、K为开。Optionally, the input variable deviation and the input variable deviation change rate include five first fuzzy sets, and the first fuzzy sets respectively represent different fuzzy states, including PB for positive large, PM for positive medium, PS for positive small, ZE for zero, NS for negative small, NM for negative medium, and NB for negative large; the expansion factor of the variable domain includes five second fuzzy sets, and the second fuzzy sets represent the control trend of the opening and closing of the solenoid valve, and the second fuzzy sets include ZE for closed, S for small, M for medium, B for large, and K for open.

本申请实施例包括以下优点:The embodiments of the present application include the following advantages:

本申请实施例提供的半主动悬架的控制方法及系统,通过根据预先建立的变阻尼减振器仿真模型,确定减振器的外特性曲线;获取路面随机扰动信息和半主动悬架的性能参数;根据半主动悬架的性能参数和路面随机扰动信息,确定模糊调节策略;根据模糊调节策略,确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节,通过建立的变阻尼减振器仿真模型,确定减振器外特性,并将减振器外特性和半主动悬架结合,针对半主动悬架参数的不确定性和路面的随机扰动,确定自适应变论域模糊PID控制策略,并根据该自适应变论域模糊PID控制策略确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节,可以有效的减小悬架动挠度、车身加速度和车身动载荷的峰值。The control method and system of the semi-active suspension provided in the embodiment of the present application determine the external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model; obtain road surface random disturbance information and performance parameters of the semi-active suspension; determine a fuzzy adjustment strategy according to the performance parameters of the semi-active suspension and the road surface random disturbance information; determine the adjusted control parameters according to the fuzzy adjustment strategy, and adjust the suspension dynamic deflection, wheel dynamic load, and body acceleration according to the adjusted control parameters, determine the external characteristics of the shock absorber through the established variable damping shock absorber simulation model, and combine the external characteristics of the shock absorber with the semi-active suspension, determine an adaptive variable domain fuzzy PID control strategy for the uncertainty of the semi-active suspension parameters and the random disturbance of the road surface, and determine the adjusted control parameters according to the adaptive variable domain fuzzy PID control strategy, and adjust the suspension dynamic deflection, wheel dynamic load, and body acceleration according to the adjusted control parameters, which can effectively reduce the peak values of the suspension dynamic deflection, body acceleration, and body dynamic load.

附图说明BRIEF DESCRIPTION OF THE DRAWINGS

为了更清楚地说明本申请实施例或现有的技术方案,下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本申请中记载的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动性的前提下,还可以根据这些附图获得其他的附图。In order to more clearly illustrate the embodiments of the present application or the existing technical solutions, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

图1为本申请一实施例中一种半主动悬架的控制方法的流程图;FIG1 is a flow chart of a control method of a semi-active suspension in one embodiment of the present application;

图2为本申请一实施例中一种半主动悬架的控制系统示意图;FIG2 is a schematic diagram of a control system of a semi-active suspension in one embodiment of the present application;

图3为本申请一实施例中1/4车辆半主动悬架系统示意图;FIG3 is a schematic diagram of a 1/4 vehicle semi-active suspension system in one embodiment of the present application;

图4为本申请一实施例中B级路面随机激励信号;FIG4 is a random excitation signal of a Class B road surface in one embodiment of the present application;

图5为本申请一实施例中自适应模糊PID控制器的设计流程图;FIG5 is a design flow chart of an adaptive fuzzy PID controller in one embodiment of the present application;

图6为本申请一实施例中的E,EC的隶属函数;FIG6 is a membership function of E and EC in an embodiment of the present application;

图7为本申请一实施例中变论域模糊控制原理图;FIG7 is a schematic diagram of a variable domain fuzzy control principle in one embodiment of the present application;

图8是本申请的一种半主动悬架的控制系统实施例的结构框图。FIG. 8 is a structural block diagram of a control system embodiment of a semi-active suspension of the present application.

具体实施方式DETAILED DESCRIPTION

为使本申请的目的、技术方案和优点更加清楚,下面将结合具体实施例及相应的附图对本申请的技术方案进行清楚、完整地描述。显然,所描述的实施例仅是本申请一部分实施例,而不是全部的实施例。基于本申请中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本申请保护的范围。In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

本申请一实施例提供一种半主动悬架的控制方法,用于对半主动悬架进行控制。本实施例的执行主体为半主动悬架的控制系统。An embodiment of the present application provides a control method for a semi-active suspension, which is used to control the semi-active suspension. The embodiment is performed by a control system of the semi-active suspension.

参照图1,示出了本申请的一种半主动悬架的控制方法实施例的步骤流程图,该方法具体可以包括如下步骤:1 , a flowchart of a control method for a semi-active suspension according to an embodiment of the present invention is shown. The method may specifically include the following steps:

S101、根据预先建立的变阻尼减振器仿真模型,确定减振器的外特性曲线;S101, determining an external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model;

具体地,预先建立的变阻尼减振器仿真模型的输入为不同的输入电流和激励速度,输出为外特性曲线。Specifically, the input of the pre-established variable damping shock absorber simulation model is different input currents and excitation speeds, and the output is an external characteristic curve.

在台架试验中,输入电流和激励速度的变化可以得到减振器不同的外特性曲线,减振器外特性的变化可以指导减振器的,根据上面通过台架指标试验台得到的CDC减振器数据模型,建立相应的变阻尼减振器仿真模型,设置与台架试验一致的结构参数,仿真得到减振器外特性曲线。In the bench test, changes in input current and excitation speed can obtain different external characteristic curves of the shock absorber. The changes in the external characteristics of the shock absorber can guide the shock absorber. According to the CDC shock absorber data model obtained through the bench index test bench above, a corresponding variable damping shock absorber simulation model is established, and the structural parameters consistent with the bench test are set to obtain the external characteristic curve of the shock absorber through simulation.

S102、获取路面随机扰动信息和半主动悬架的性能参数;S102, obtaining road surface random disturbance information and performance parameters of a semi-active suspension;

其中,路面随机扰动信息为路面不平度系数的标识。Among them, the road surface random disturbance information is an indicator of the road surface roughness coefficient.

具体地,半主动悬架的性能参数至少包括悬架动挠度、车轮动载荷、车身加速度中的一种或多种。Specifically, the performance parameters of the semi-active suspension include at least one or more of suspension dynamic deflection, wheel dynamic load, and vehicle body acceleration.

S103、根据半主动悬架的性能参数和路面随机扰动信息,确定模糊调节策略;S103, determining a fuzzy adjustment strategy according to performance parameters of the semi-active suspension and random disturbance information of the road surface;

其中,预先建立的模糊调节策略包括通过输入变量偏差和输入变量偏差变化率,确定对应的变论域的伸缩因子。The pre-established fuzzy adjustment strategy includes determining the expansion factor of the corresponding variable domain through the input variable deviation and the input variable deviation change rate.

具体地,输入变量偏差和输入变量偏差变化率包括五个第一模糊集,第一模糊集分别表示不同的模糊状态,第一模糊集包括PB为正大、PM为正中、PS为正小、ZE为零、NS为负小、NM为负中、NB为负大;变论域的伸缩因子包括五个第二模糊集,第二模糊集表示对电磁阀开闭控制趋势,第二模糊集包括ZE为闭、S为小、M为中、B为大、K为开。Specifically, the input variable deviation and the input variable deviation change rate include five first fuzzy sets, and the first fuzzy sets respectively represent different fuzzy states, including PB for positive large, PM for positive medium, PS for positive small, ZE for zero, NS for negative small, NM for negative medium, and NB for negative large; the expansion factor of the variable domain includes five second fuzzy sets, and the second fuzzy set represents the control trend of the opening and closing of the solenoid valve, and the second fuzzy set includes ZE for closed, S for small, M for medium, B for large, and K for open.

具体地,半主动悬架的控制系统根据半主动悬架的性能参数和路面随机扰动信息,确定不同的模糊调节策略,也就是说,针对不同的性能参数和路面随机扰动信息,得到不同的模糊调节策略,即自适应变论域模糊PID控制策略。Specifically, the control system of the semi-active suspension determines different fuzzy adjustment strategies according to the performance parameters of the semi-active suspension and the random disturbance information of the road surface. That is to say, different fuzzy adjustment strategies are obtained for different performance parameters and random disturbance information of the road surface, namely, the adaptive variable universe fuzzy PID control strategy.

S104、根据模糊调节策略,确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节。S104: Determine adjusted control parameters according to the fuzzy adjustment strategy, and adjust the suspension dynamic deflection, wheel dynamic load, and vehicle body acceleration according to the adjusted control parameters.

具体地,该模糊调节策略,可以重新计算PID的调节参数,得到调节后的控制参数,通过调节后的控制参数,对半主动悬架的性能参数进行调节,即对悬架动挠度、车轮动载荷、车身加速度进行调节。Specifically, the fuzzy adjustment strategy can recalculate the adjustment parameters of PID to obtain the adjusted control parameters. Through the adjusted control parameters, the performance parameters of the semi-active suspension are adjusted, that is, the suspension dynamic deflection, wheel dynamic load, and vehicle body acceleration are adjusted.

本申请实施例提供的半主动悬架的控制方法,通过根据预先建立的变阻尼减振器仿真模型,确定减振器的外特性曲线;获取路面随机扰动信息和半主动悬架的性能参数;根据半主动悬架的性能参数和路面随机扰动信息,确定模糊调节策略;根据模糊调节策略,确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节,通过建立的变阻尼减振器仿真模型,确定减振器外特性,并将减振器外特性和半主动悬架结合,针对半主动悬架参数的不确定性和路面的随机扰动,确定自适应变论域模糊PID控制策略,并根据该自适应变论域模糊PID控制策略确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节,可以有效的减小悬架动挠度、车身加速度和车身动载荷的峰值。The control method of the semi-active suspension provided in the embodiment of the present application determines the external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model; obtains road surface random disturbance information and performance parameters of the semi-active suspension; determines a fuzzy adjustment strategy according to the performance parameters of the semi-active suspension and the road surface random disturbance information; determines the adjusted control parameters according to the fuzzy adjustment strategy, and adjusts the suspension dynamic deflection, wheel dynamic load, and body acceleration according to the adjusted control parameters, determines the external characteristics of the shock absorber through the established variable damping shock absorber simulation model, and combines the external characteristics of the shock absorber with the semi-active suspension, determines an adaptive variable domain fuzzy PID control strategy for the uncertainty of the semi-active suspension parameters and the random disturbance of the road surface, determines the adjusted control parameters according to the adaptive variable domain fuzzy PID control strategy, and adjusts the suspension dynamic deflection, wheel dynamic load, and body acceleration according to the adjusted control parameters, which can effectively reduce the peak values of the suspension dynamic deflection, body acceleration, and body dynamic load.

如图2所示的一种路面自适应半主动悬架控制系统,该半主动悬架控制系统执行如下步骤:A road surface adaptive semi-active suspension control system as shown in FIG2 , the semi-active suspension control system performs the following steps:

步骤1、建立减振器模型,选择CDC减振器作为研究对象,设定振动行程为40mm,通过台架指标试验台对CDC减振器进行试验,输入正弦激励信号,并拾取激励。Step 1: Establish a shock absorber model, select the CDC shock absorber as the research object, set the vibration stroke to 40 mm, test the CDC shock absorber through the bench index test bench, input a sinusoidal excitation signal, and pick up the excitation.

在台架试验中,输入电流和激励速度的变化可以得到减振器不同的外特性曲线,减振器外特性的变化可以指导减振器的设计。In bench tests, changes in input current and excitation speed can produce different external characteristic curves of the shock absorber. Changes in the external characteristics of the shock absorber can guide the design of the shock absorber.

测试得到的硬件参数硬件如表1所示:The hardware parameters obtained from the test are shown in Table 1:

表1Table 1

Figure BDA0004067056740000051
Figure BDA0004067056740000051

根据上面通过台架指标试验台得到的CDC减振器数据模型,建立相应的变阻尼减振器仿真模型,设置与台架试验一致的结构参数,仿真得到减振器外特性曲线。According to the CDC shock absorber data model obtained through the bench index test bench, a corresponding variable damping shock absorber simulation model is established, the structural parameters consistent with the bench test are set, and the shock absorber external characteristic curve is obtained by simulation.

二者的实验对比如表2所示:The experimental comparison of the two is shown in Table 2:

表2Table 2

Figure BDA0004067056740000052
Figure BDA0004067056740000052

Figure BDA0004067056740000061
Figure BDA0004067056740000061

从表2中可以看出来,试验结果与仿真结果的力值与误差范围基本吻合,最大误差为11.8%,最小误差为2.0%,以上分析可以说明减振器模型的准确性,表明该模型可以用于半主动悬架的研究。It can be seen from Table 2 that the force values and error ranges of the test results and simulation results are basically consistent, with the maximum error being 11.8% and the minimum error being 2.0%. The above analysis can illustrate the accuracy of the shock absorber model and shows that the model can be used for the study of semi-active suspension.

步骤2、建立1/4车辆半主动悬架动力学简化模型,针对上面的半主动悬架模型,选取B级路面上不同车速的激励图形作为半主动悬架的激励信号,建立随机路面扰动模型,并作为初始激励信号源输入到耦合CDC减振器的半主动悬架模型中。Step 2: Establish a simplified dynamic model of the 1/4 vehicle semi-active suspension. For the above semi-active suspension model, select the excitation graphs of different vehicle speeds on Class B road as the excitation signal of the semi-active suspension, establish a random road disturbance model, and input it into the semi-active suspension model of the coupled CDC shock absorber as the initial excitation signal source.

1/4车辆半主动动力学简化模型如图3所示,根据半主动悬挂物理模型和牛顿第二定律,得到簧载质量和簧下质量在竖直Z方向的运动学微分方程为:The simplified semi-active dynamics model of the quarter vehicle is shown in Figure 3. According to the physical model of the semi-active suspension and Newton's second law, the kinematic differential equations of the sprung mass and the unsprung mass in the vertical Z direction are obtained as follows:

Figure BDA0004067056740000062
Figure BDA0004067056740000062

Figure BDA0004067056740000063
Figure BDA0004067056740000063

其中,Mb为簧载质量;Mu为簧下质量;Ks为悬架弹簧刚度;Kw为轮胎刚度;Cs为悬架阻尼系数;Zu为非簧载质量位移;Zb为簧载质量位移;Zw为路面输入位移;U为半主动悬架的阻尼力。Among them, Mb is the sprung mass; Mu is the unsprung mass; Ks is the suspension spring stiffness; Kw is the tire stiffness; Cs is the suspension damping coefficient; Zu is the unsprung mass displacement; Zb is the sprung mass displacement; Zw is the road input displacement; and U is the damping force of the semi-active suspension.

可得系统的状态方程为:The state equation of the system is:

Figure BDA0004067056740000064
Figure BDA0004067056740000064

其中A满足:Where A satisfies:

Figure BDA0004067056740000065
Figure BDA0004067056740000065

B满足:B satisfies:

Figure BDA0004067056740000071
Figure BDA0004067056740000071

F满足:F satisfies:

F=[00-10]TF = [00-10] T .

其中:

Figure BDA0004067056740000072
为路面的输入。in:
Figure BDA0004067056740000072
Input for the road surface.

选取车身振动加速度

Figure BDA0004067056740000073
悬架动挠度(Zb-Zu);轮胎动变形(Zu-Zw)作为输出变量。Select the body vibration acceleration
Figure BDA0004067056740000073
Suspension dynamic deflection (Z b -Z u ); tire dynamic deformation (Z u -Z w ) are used as output variables.

则系统的输出方程为:Then the output equation of the system is:

Y=CX+DUY=CX+DU

其中Y满足:Where Y satisfies:

Figure BDA0004067056740000074
Figure BDA0004067056740000074

其中C满足:Where C satisfies:

Figure BDA0004067056740000075
Figure BDA0004067056740000075

D满足:D satisfies:

Figure BDA0004067056740000076
Figure BDA0004067056740000076

按照国际标准化不同路况下的时域扰动曲线不同,并以路面PSD的形式进行描述。通常采用下式拟合路面激励的功率谱:According to international standards, the time domain disturbance curves under different road conditions are different and are described in the form of road surface PSD. The following formula is usually used to fit the power spectrum of road surface excitation:

Figure BDA0004067056740000077
Figure BDA0004067056740000077

其中:空间频率为n(m-1);参考空间频率为n0;通常取n0=0.1(m-1)。路面不平度系数为Gq(n0)(m3),为高斯白噪声,频率指数为2。Where: the spatial frequency is n(m -1 ); the reference spatial frequency is n 0 ; usually n0=0.1(m -1 ). The road roughness coefficient is G q (n 0 )(m 3 ), which is Gaussian white noise with a frequency index of 2.

GB-7031-1986标准将路面不平度系数分为A~H共8个等级,其中A级路面为对应的高速公路及其路面状况,A级路面为最佳路面状况,E级路面为未铺装路面,H级路面为最差路面状况。The GB-7031-1986 standard divides the road roughness coefficient into 8 levels from A to H, among which Class A road surface is the corresponding expressway and its road condition, Class A road surface is the best road condition, Class E road surface is unpaved road surface, and Class H road surface is the worst road condition.

路面不平度八级分级标准如表3所示:The eight-level classification standard for road roughness is shown in Table 3:

表3Table 3

Figure BDA0004067056740000081
Figure BDA0004067056740000081

针对上述半主动悬架模型,建立随机路面扰动模型的滤波白噪声激励信号,选取B级路面上车速为30km/h、70km/h、120km/h时的激励图形作为半主动悬架的激励信号。For the above semi-active suspension model, a filtered white noise excitation signal of the random road disturbance model is established, and the excitation patterns at speeds of 30km/h, 70km/h, and 120km/h on a Class B road are selected as the excitation signals of the semi-active suspension.

路面激励的时域信号如下:The time domain signal of road surface excitation is as follows:

Figure BDA0004067056740000082
Figure BDA0004067056740000082

其中,f0为下截止频率(Hz),q(t)为路面高度(m),Gq(n0)为路面不平度系数(m3),v为车辆行驶速度(m/s),w(t)为白噪声信号。Where f 0 is the lower cutoff frequency (Hz), q(t) is the road height (m), G q (n 0 ) is the road roughness coefficient (m 3 ), v is the vehicle speed (m/s), and w(t) is the white noise signal.

B级路面随机激励信号如图4所示。The random excitation signal of Class B road surface is shown in Figure 4.

步骤3、建立一个自适应变论域模糊PID控制器,PID控制器直接与悬架系统连接,模糊控制器连接PID控制器。PID控制器通过对PID参数Kp、Ki和Kd的实时调整,使半主动悬架分别对悬架动挠度、车轮动载荷、车身加速度进行调节。模糊控制器可以根据汽车的动态性能实时调整PID控制器参数,提供了两输入三输出的二维模糊控制器,模糊控制器输入变量为偏差E和偏差变化率EC,输出变量为PID控制器参数的修正量Kp、Ki和Kd,如图5所示。Step 3, establish an adaptive variable domain fuzzy PID controller, the PID controller is directly connected to the suspension system, and the fuzzy controller is connected to the PID controller. The PID controller adjusts the PID parameters Kp, Ki and Kd in real time, so that the semi-active suspension adjusts the suspension dynamic deflection, wheel dynamic load and body acceleration respectively. The fuzzy controller can adjust the PID controller parameters in real time according to the dynamic performance of the car, and provides a two-input and three-output two-dimensional fuzzy controller. The input variables of the fuzzy controller are the deviation E and the deviation change rate EC, and the output variables are the correction values of the PID controller parameters Kp, Ki and Kd, as shown in Figure 5.

依据实际控制对象,车体垂直方向的振动速度偏差信号和振动加速度偏差变化率均为数值形式,因此对输入输出变量进行模糊化处理。According to the actual control object, the vibration velocity deviation signal and the vibration acceleration deviation change rate of the vehicle body in the vertical direction are both in numerical form, so the input and output variables are fuzzy processed.

对模糊控制器的输入变量E、EC采用五个模糊集表示它们的模糊状态,在设计中,输入变量E和EC与输出变量Kp、Ki和Kd的模糊论域均设为[-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6],对于PID控制E、EC的模糊子集为[NB、NM、NS、ZO、PS、PM、PB]。Five fuzzy sets are used to represent the fuzzy states of the input variables E and EC of the fuzzy controller. In the design, the fuzzy domains of the input variables E and EC and the output variables Kp, Ki and Kd are set to [-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6]. For PID control, the fuzzy subsets of E and EC are [NB, NM, NS, ZO, PS, PM, PB].

根据之前对悬架的分析,隶属函数均选为三角隶属度函数,选择mamdani型min-max法作为模糊推理方法,选择重心法作为模糊决策,可得E,EC的隶属度函数如图6所示。According to the previous analysis of the suspension, the membership functions are all selected as triangular membership functions, the Mamdani type min-max method is selected as the fuzzy reasoning method, and the center of gravity method is selected as the fuzzy decision. The membership functions of E and EC are shown in Figure 6.

隶属函数表达方式为:The membership function is expressed as:

Figure BDA0004067056740000091
Figure BDA0004067056740000091

以偏差E和EC作为控制器的输入,得到修正后的PID参数为:Taking the deviation E and EC as the input of the controller, the corrected PID parameters are:

Kzp=Kp0+qkpKp K zp =K p0 +q kp K p

Kzi=Ki0+qkiKi K zi = K i0 + q ki K i

Kzd=Kd0+qkdKd K zd =K d0 +q kd K d

其中:式中:Kzp、Kzi、Kzd为PID最终参数的设定值;Kp0、Ki0、Kd0为PID初始参数设定值;qkp、qki和qkd为修正系数。Where: In the formula: Kzp , Kzi , Kzd are the setting values of the final PID parameters; Kp0 , Ki0 , Kd0 are the setting values of the initial PID parameters; qkp , qki and qkd are the correction coefficients.

为避免输入输出变量相对于论域过大或过小的现象,提出变论域模糊控制方法,建立一个自适应变论域模糊PID控制器,自适应变论域模糊控制原理图如图7所示。In order to avoid the phenomenon that the input and output variables are too large or too small relative to the universe, a variable universe fuzzy control method is proposed, and an adaptive variable universe fuzzy PID controller is established. The principle diagram of the adaptive variable universe fuzzy control is shown in Figure 7.

xi=[-E、E](i=1,2…,n)为输入变量xi(i=1,2,…,n)的论域,Y=[-U,U]为输出变量y的论域。xi=[-E, E](i=1,2…,n) is the domain of input variables xi(i=1,2,…,n), and Y=[-U,U] is the domain of output variables y.

模糊输出响应可近似为下式:The fuzzy output response can be approximated as follows:

Figure BDA0004067056740000092
Figure BDA0004067056740000092

可变化为:Can be changed to:

Xi(xi)=[-αi(xi)Eii(xi)Ei]X i (x i )=[-α i (x i )E ii (x i )E i ]

Y(y)=[-β(y)U,β(y)U]Y(y)=[-β(y)U,β(y)U]

其中:变量αi(xi)(i=1,2,...n),β(y)分别为Xi和Y的展开因子,αi(xi)=1-λexp(-kx2),λ∈(0,1),k>0。Wherein: variables α i ( xi ) (i=1,2,...n), β(y) are the expansion factors of Xi and Y respectively, α i ( xi )=1-λexp(-kx 2 ), λ∈(0,1), k>0.

其中关于建立的自适应变论域模糊PID控制器,所选取的控制器的输入变量为偏差E和EC,控制器的输出分别为变论域的伸缩因子。通过控制器,使得代表悬架舒适性的悬架动挠度和车身加速度,代表安全性的车身动载荷三个指标均有所优化。保证了输入输出理论控制量论域随着误差的变化而相应的扩张或膨胀,使得模糊控制具有适应控制对象变化的能力,不断在更精确的局部区域逼近理想的控制输出。Among them, the input variables of the established adaptive variable universe fuzzy PID controller are the deviation E and EC, and the output of the controller is the expansion factor of the variable universe. Through the controller, the three indicators of suspension dynamic deflection and body acceleration representing suspension comfort, and body dynamic load representing safety are optimized. It is ensured that the input and output theoretical control quantity domain expands or expands accordingly with the change of error, so that the fuzzy control has the ability to adapt to the change of the control object and constantly approaches the ideal control output in a more precise local area.

依据实际控制对象,对控制器的输入偏差E和EC采用五个模糊集表示它们的模糊状态,相应的模糊子集为PB为正大、PM为正中、PS为正小、ZE为零、NS为负小、NM为负中、NB为负大;而对于输出的伸缩因子采用五个模糊集表示对电磁阀开闭控制趋势,即ZE为闭、S为小、M为中、B为大、K为开;。在设计中,输入变量输入和输出的模糊论域均设为[-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6]。According to the actual control object, five fuzzy sets are used to represent the fuzzy states of the controller input deviations E and EC. The corresponding fuzzy subsets are PB for positive large, PM for positive medium, PS for positive small, ZE for zero, NS for negative small, NM for negative medium, and NB for negative large; and five fuzzy sets are used to represent the control trend of the solenoid valve opening and closing for the output expansion factor, namely, ZE for closed, S for small, M for medium, B for large, and K for open. In the design, the fuzzy domains of the input variables input and output are set to [-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6].

根据之前对悬架运动过程分析,可以得到模糊规则表,如下表4所示:According to the previous analysis of the suspension motion process, the fuzzy rule table can be obtained, as shown in Table 4 below:

表4Table 4

Figure BDA0004067056740000101
Figure BDA0004067056740000101

,对于模糊规则表具体可描述为:当输入变量E为NB,另一个输入变量EC为NB,NM,NS,ZE,PS,PM,PB,对应的输出变量分别为PB,PB,PM,PS,PM,PB,PB;当输入变量E为NM,另一个输入变量EC为NB,NM,NS,ZE,PS,PM,PB,对应的输出变量分别为PB,PM,PM,PS,PM,PM,PB;当输入变量E为NS,另一个输入变量EC为NB,NM,NS,ZE,PS,PM,PB对应的输出变量分别为PM,PM,PS,ZO,PS,PM,PM;当输入变量E为ZE,另一个输入变量EC为NB,NM,NS,ZE,PS,PM,PB,对应的输出变量分别为PS,PS,ZO,ZO,ZO,PS,PS;当输入变量E为PS,另一个输入变量EC为NB,NM,NS,ZE,PS,PM,PB,对应的输出变量分别为PM,PM,PS,ZO,PS,PM,PM;当输入变量E为PM,另一个输入变量EC为NB,NM,NS,ZE,PS,PM,PB,对应的输出变量分别为PB,PM,PM,PS,PM,PM,PB;当输入变量E为PB,另一个输入变量EC为NB,NM,NS,ZE,PS,PM,PB,对应的输出变量分别为PB,PB,PM,PS,PM,PB,PB。,The fuzzy rule table can be specifically described as follows: when the input variable E is NB, the other input variable EC is NB, NM, NS, ZE, PS, PM, PB, the corresponding output variables are PB, PB, PM, PS, PM, PB, PB; when the input variable E is NM, the other input variable EC is NB, NM, NS, ZE, PS, PM, PB, the corresponding output variables are PB, PM, PM, PS, PM, PM, PB; when the input variable E is NS, the other input variable EC is NB, NM, NS, ZE, PS, PM, PB, the corresponding output variables are PM, PM, PS, ZO, PS, PM, PM; when the input variable E is ZE, the other input variable EC is NB, NM, NS, ZE, PS, PM, PB, the corresponding output variables are PS, PS, ZO, ZO, ZO, PS, PS, PS respectively; when the input variable E is PS and the other input variable EC is NB, NM, NS, ZE, PS, PM, PB, the corresponding output variables are PM, PM, PS, ZO, PS, PM, PM respectively; when the input variable E is PM and the other input variable EC is NB, NM, NS, ZE, PS, PM, PB, the corresponding output variables are PB, PM, PM, PS, PM, PM, PB respectively; when the input variable E is PB and the other input variable EC is NB, NM, NS, ZE, PS, PM, PB, the corresponding output variables are PB, PB, PM, PS, PM, PB, PB respectively.

步骤4、为了对所设计的控制器效果进行验证,在Matlab/Simulink环境下对建立的整个悬架系统进行仿真分析,将建立的道路模型系统作为初始激励信号源输入到半主动悬架模型中,将变论域自适应模糊PID控制模型输入到悬架系统的控制模块中,并固定相应的参数,采用变论域模糊控制器,对控制系统的输入输出场进行自整定;采用自适应模糊PID控制,改善系统的动静态特性。Step 4. In order to verify the effect of the designed controller, the entire suspension system is simulated and analyzed in the Matlab/Simulink environment. The established road model system is input into the semi-active suspension model as the initial excitation signal source. The variable domain adaptive fuzzy PID control model is input into the control module of the suspension system. The corresponding parameters are fixed and the variable domain fuzzy controller is used to self-tune the input and output fields of the control system. Adaptive fuzzy PID control is used to improve the dynamic and static characteristics of the system.

控制系统分别监测系统相应的输出变量,即半主动悬架的性能参数,包括:悬架动挠度、车体加速度、车体动载荷等评价指标。The control system monitors the corresponding output variables of the system, namely the performance parameters of the semi-active suspension, including evaluation indicators such as suspension dynamic deflection, vehicle body acceleration, and vehicle body dynamic load.

基于B类路面激励,选取3种不同的车辆行驶工况,分别为低速行驶(30km/h)、中速行驶(70km/h)、高速行驶(120km/h)。分别对PID控制(PC)、模糊控制(FC)、变论域模糊PID自适应控制(VAC)下选取的车身加速度、悬架扰动、车轮动载荷3个评价指标进行仿真对比。在此基础上,对仿真结果进一步进行分析和处理,得其RMS值对比如表5所示。Based on the B-type road excitation, three different vehicle driving conditions are selected, namely low-speed driving (30km/h), medium-speed driving (70km/h), and high-speed driving (120km/h). The three evaluation indicators of vehicle body acceleration, suspension disturbance, and wheel dynamic load selected under PID control (PC), fuzzy control (FC), and variable universe fuzzy PID adaptive control (VAC) are simulated and compared. On this basis, the simulation results are further analyzed and processed, and the RMS value comparison is shown in Table 5.

表5Table 5

Figure BDA0004067056740000111
Figure BDA0004067056740000111

从表5中可以看出,三种控制策略均可通过VAC控制器降低车身加速度、悬架动挠度、车轮动载荷在B级路面激励下的幅值,所有案例均表明,与其他方法相比,VAC控制器能够取得良好的优化效果。It can be seen from Table 5 that the three control strategies can reduce the amplitude of vehicle body acceleration, suspension dynamic deflection, and wheel dynamic load under Class B road excitation through the VAC controller. All cases show that the VAC controller can achieve good optimization results compared with other methods.

可以看到,自适应变论域模糊PID半主动悬架控制系统的车身加速度、悬架动挠度、车轮动载荷相对于传统单模糊PID控制系统和模糊控制均有大幅提高,在舒适性、平顺性和操纵稳定性方面有大幅改善。It can be seen that the body acceleration, suspension dynamic deflection and wheel dynamic load of the adaptive variable domain fuzzy PID semi-active suspension control system are greatly improved compared with the traditional single fuzzy PID control system and fuzzy control, and there are significant improvements in comfort, smoothness and handling stability.

综上,本发明实施例的一种自适应变论域模糊PID半主动悬架控制系统,通过分析耦合CDC减振器的半主动悬架系统的动态性能,得到控制变量,推导出半主动悬架的数学函数。此外,建立了基于减振器台架试验的半主动悬架仿真模型,从而使得车辆半主动悬架的阻尼控制更加高效和节能。首先利用台架试验台测量外特性并建立CDC减振器仿真模型。然后选取某一路面不同车速的激励图形作为车辆半主动悬架动力学模型的激励信号获得随机路面扰动模型。建立一个自适应变论域模糊PID控制器,PID控制器直接与悬架系统连接,模糊控制器连接PID控制器。该模糊控制器以偏差E和EC作为控制器的输入,采用变论域模糊控制器,对输入输出变量进行模糊化处理。将建立的道路模型系统作为初始激励信号源输入到耦合CDC减振器的半主动悬架模型中,进而将变论域自适应模糊PID控制模型输入到悬架系统的控制模块中,并固定相应的参数,从而快速响应不同路面扰动下驾驶舒适性和安全性的不同性能需求。本发明可以有效的减小后悬架动挠度、车身加速度和车身动载荷的峰值,提高了车辆行驶平顺性。In summary, an adaptive variable universe fuzzy PID semi-active suspension control system of an embodiment of the present invention obtains control variables and derives mathematical functions of the semi-active suspension by analyzing the dynamic performance of the semi-active suspension system coupled with the CDC shock absorber. In addition, a semi-active suspension simulation model based on the shock absorber bench test is established, so that the damping control of the vehicle semi-active suspension is more efficient and energy-saving. First, the external characteristics are measured using a bench test bench and a CDC shock absorber simulation model is established. Then, an excitation graph of different vehicle speeds on a certain road surface is selected as an excitation signal for the vehicle semi-active suspension dynamics model to obtain a random road disturbance model. An adaptive variable universe fuzzy PID controller is established, the PID controller is directly connected to the suspension system, and the fuzzy controller is connected to the PID controller. The fuzzy controller uses the deviation E and EC as the input of the controller, and uses a variable universe fuzzy controller to fuzzify the input and output variables. The established road model system is input as the initial excitation signal source into the semi-active suspension model coupled with the CDC shock absorber, and then the variable universe adaptive fuzzy PID control model is input into the control module of the suspension system, and the corresponding parameters are fixed, so as to quickly respond to different performance requirements of driving comfort and safety under different road disturbances. The present invention can effectively reduce the dynamic deflection of the rear suspension, the acceleration of the vehicle body and the peak value of the dynamic load of the vehicle body, thereby improving the driving smoothness of the vehicle.

本发明实施例在台架指标试验台对CDC减振器进行试验,建立相应的变阻尼减振器仿真模型,设置与台架试验一致的结构参数,仿真得到减振器外特性曲线。建立的1/4车辆半主动悬架动力学模型,并选取某一路面不同车速的激励图形作为该半主动悬架的激励信号,建立随机路面扰动模型。提供了两输入三输出的二维模糊控制器,以偏差E和EC作为控制器的输入,并对输入输出变量进行模糊化处理。The embodiment of the present invention tests the CDC shock absorber on a bench index test bench, establishes a corresponding variable damping shock absorber simulation model, sets structural parameters consistent with the bench test, and simulates the external characteristic curve of the shock absorber. A 1/4 vehicle semi-active suspension dynamics model is established, and an excitation graph of different vehicle speeds on a certain road surface is selected as the excitation signal of the semi-active suspension, and a random road disturbance model is established. A two-input and three-output two-dimensional fuzzy controller is provided, with deviations E and EC as the input of the controller, and the input and output variables are fuzzy processed.

将建立的道路模型系统作为初始激励信号源输入到半主动悬架模型中,将变论域自适应模糊PID控制模型输入到悬架系统的控制模块中,并固定相应的参数,采用变论域模糊控制器。对控制系统的输入输出场进行自整定,提高控制精度;采用自适应模糊PID控制,改善系统的动静态特性。The established road model system is used as the initial excitation signal source to input into the semi-active suspension model, and the variable universe adaptive fuzzy PID control model is input into the control module of the suspension system, and the corresponding parameters are fixed, and the variable universe fuzzy controller is used. The input and output fields of the control system are self-tuned to improve the control accuracy; the adaptive fuzzy PID control is used to improve the dynamic and static characteristics of the system.

与现有的技术比较,本申请实施例可实现:Compared with the existing technology, the embodiments of the present application can achieve:

通过台架实验和仿真得出减振器外特性,并将减振器外特性和半主动悬架结合,针对悬架参数的不确定性和路面的随机扰动,提出了一种自适应变论域模糊PID控制策略,可以有效的减小后悬架动挠度、车身加速度和车身动载荷的峰值。The external characteristics of the shock absorber are obtained through bench experiments and simulations, and combined with the semi-active suspension. Aiming at the uncertainty of suspension parameters and random disturbances of the road surface, an adaptive variable universe fuzzy PID control strategy is proposed, which can effectively reduce the peak value of the rear suspension dynamic deflection, body acceleration and body dynamic load.

通过有效结合路面信息和半主动悬架状态,设计自适应变论域模糊PID控制器,快速响应不同路面扰动下驾驶舒适性和安全性的不同性能需求,提高系统的减振和稳定性能。By effectively combining road surface information and semi-active suspension status, an adaptive variable universe fuzzy PID controller is designed to quickly respond to different performance requirements of driving comfort and safety under different road disturbances, thereby improving the vibration reduction and stability performance of the system.

建立起了悬架系统与减振器的直接关系,在台架试验中,输入电流和激励速度的变化可得到减振器不同的外特性曲线,可以指导减振器的设计,相较于单一的减振器的选取,拥有更加全面的控制效果。A direct relationship between the suspension system and the shock absorber has been established. In the bench test, changes in input current and excitation speed can obtain different external characteristic curves of the shock absorber, which can guide the design of the shock absorber. Compared with the selection of a single shock absorber, it has a more comprehensive control effect.

本申请另一实施例提供一种半主动悬架的控制系统,用于执行上述实施例提供的半主动悬架的控制方法。Another embodiment of the present application provides a control system for a semi-active suspension, which is used to execute the control method for the semi-active suspension provided in the above embodiment.

参照图8,示出了本申请的一种半主动悬架的控制系统实施例的结构框图,该装置具体可以包括如下模块:第一确定模块801、获取模块802、第二确定模块803和调节模块804,其中:8 , a block diagram of a control system embodiment of a semi-active suspension of the present application is shown. The device may specifically include the following modules: a first determination module 801, an acquisition module 802, a second determination module 803 and an adjustment module 804, wherein:

第一确定模块801用于根据预先建立的变阻尼减振器仿真模型,确定减振器的外特性曲线;The first determination module 801 is used to determine the external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model;

获取模块802用于获取路面随机扰动信息和半主动悬架的性能参数;The acquisition module 802 is used to acquire road surface random disturbance information and performance parameters of the semi-active suspension;

第二确定模块803用于根据半主动悬架的性能参数和路面随机扰动信息,确定模糊调节策略;The second determination module 803 is used to determine the fuzzy adjustment strategy according to the performance parameters of the semi-active suspension and the random disturbance information of the road surface;

调节模块804用于根据模糊调节策略,确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节。The adjustment module 804 is used to determine the adjusted control parameters according to the fuzzy adjustment strategy, and adjust the suspension dynamic deflection, wheel dynamic load, and vehicle body acceleration according to the adjusted control parameters.

本申请实施例提供的半主动悬架的控制系统,通过根据预先建立的变阻尼减振器仿真模型,确定减振器的外特性曲线;获取路面随机扰动信息和半主动悬架的性能参数;根据半主动悬架的性能参数和路面随机扰动信息,确定模糊调节策略;根据模糊调节策略,确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节,通过建立的变阻尼减振器仿真模型,确定减振器外特性,并将减振器外特性和半主动悬架结合,针对半主动悬架参数的不确定性和路面的随机扰动,确定自适应变论域模糊PID控制策略,并根据该自适应变论域模糊PID控制策略确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节,可以有效的减小悬架动挠度、车身加速度和车身动载荷的峰值。The control system of the semi-active suspension provided in the embodiment of the present application determines the external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model; obtains road surface random disturbance information and performance parameters of the semi-active suspension; determines a fuzzy adjustment strategy according to the performance parameters of the semi-active suspension and the random disturbance information of the road surface; determines the adjusted control parameters according to the fuzzy adjustment strategy, and adjusts the suspension dynamic deflection, wheel dynamic load, and body acceleration according to the adjusted control parameters, determines the external characteristics of the shock absorber through the established variable damping shock absorber simulation model, and combines the external characteristics of the shock absorber with the semi-active suspension, determines an adaptive variable domain fuzzy PID control strategy for the uncertainty of the semi-active suspension parameters and the random disturbance of the road surface, determines the adjusted control parameters according to the adaptive variable domain fuzzy PID control strategy, and adjusts the suspension dynamic deflection, wheel dynamic load, and body acceleration according to the adjusted control parameters, which can effectively reduce the peak values of the suspension dynamic deflection, body acceleration, and body dynamic load.

本申请又一实施例对上述实施例提供的半主动悬架的控制系统做进一步补充说明。Another embodiment of the present application further supplements the control system of the semi-active suspension provided in the above embodiment.

可选地,预先建立的变阻尼减振器仿真模型的输入为不同的输入电流和激励速度,输出为外特性曲线。Optionally, the input of the pre-established variable damping shock absorber simulation model is different input currents and excitation speeds, and the output is an external characteristic curve.

可选地,路面随机扰动信息为路面不平度系数的标识。Optionally, the road surface random disturbance information is an identifier of a road surface roughness coefficient.

可选地,预先建立的模糊调节策略包括通过输入变量偏差和输入变量偏差变化率,确定对应的变论域的伸缩因子。Optionally, the pre-established fuzzy adjustment strategy includes determining a corresponding scaling factor of the variable universe through an input variable deviation and a rate of change of the input variable deviation.

可选地,输入变量偏差和输入变量偏差变化率包括五个第一模糊集,第一模糊集分别表示不同的模糊状态,第一模糊集包括PB为正大、PM为正中、PS为正小、ZE为零、NS为负小、NM为负中、NB为负大;变论域的伸缩因子包括五个第二模糊集,第二模糊集表示对电磁阀开闭控制趋势,第二模糊集包括ZE为闭、S为小、M为中、B为大、K为开。Optionally, the input variable deviation and the input variable deviation change rate include five first fuzzy sets, the first fuzzy sets respectively represent different fuzzy states, the first fuzzy sets include PB for positive large, PM for positive middle, PS for positive small, ZE for zero, NS for negative small, NM for negative middle, and NB for negative large; the expansion factor of the variable domain includes five second fuzzy sets, the second fuzzy sets represent the control trend of the opening and closing of the solenoid valve, the second fuzzy sets include ZE for closed, S for small, M for middle, B for large, and K for open.

对于装置实施例而言,由于其与方法实施例基本相似,所以描述的比较简单,相关之处参见方法实施例的部分说明即可。As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

本申请实施例提供的半主动悬架的控制系统,通过根据预先建立的变阻尼减振器仿真模型,确定减振器的外特性曲线;获取路面随机扰动信息和半主动悬架的性能参数;根据半主动悬架的性能参数和路面随机扰动信息,确定模糊调节策略;根据模糊调节策略,确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节,通过建立的变阻尼减振器仿真模型,确定减振器外特性,并将减振器外特性和半主动悬架结合,针对半主动悬架参数的不确定性和路面的随机扰动,确定自适应变论域模糊PID控制策略,并根据该自适应变论域模糊PID控制策略确定调节后的控制参数,并根据调节后的控制参数,对悬架动挠度、车轮动载荷、车身加速度进行调节,可以有效的减小悬架动挠度、车身加速度和车身动载荷的峰值。The control system of the semi-active suspension provided in the embodiment of the present application determines the external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model; obtains road surface random disturbance information and performance parameters of the semi-active suspension; determines a fuzzy adjustment strategy according to the performance parameters of the semi-active suspension and the random disturbance information of the road surface; determines the adjusted control parameters according to the fuzzy adjustment strategy, and adjusts the suspension dynamic deflection, wheel dynamic load, and body acceleration according to the adjusted control parameters, determines the external characteristics of the shock absorber through the established variable damping shock absorber simulation model, and combines the external characteristics of the shock absorber with the semi-active suspension, determines an adaptive variable domain fuzzy PID control strategy for the uncertainty of the semi-active suspension parameters and the random disturbance of the road surface, determines the adjusted control parameters according to the adaptive variable domain fuzzy PID control strategy, and adjusts the suspension dynamic deflection, wheel dynamic load, and body acceleration according to the adjusted control parameters, which can effectively reduce the peak values of the suspension dynamic deflection, body acceleration, and body dynamic load.

应该指出,上述详细说明都是示例性的,旨在对本申请提供进一步的说明。除非另有指明,本文使用的所有技术和科学术语均具有与本申请所属技术领域的普通技术人员的通常理解所相同的含义。It should be noted that the above detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present application belongs.

需要注意的是,这里所使用的术语仅是为了描述具体实施方式,而非意图限制根据本申请的示例性实施方式。如在这里所使用的,除非上下文另外明确指出,否则单数形式也意图包括复数形式。此外,还应当理解的是,当在本说明书中使用术语“包含”和/或“包括”时,其指明存在特征、步骤、操作、器件、组件和/或它们的组合。It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprise" and/or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and/or combinations thereof.

需要说明的是,本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象,而不必用于描述特定的顺序或先后次序。应该理解这样使用的术语在适当情况下可以互换,以便这里描述的本申请的实施方式能够以除了在这里图示或描述的那些以外的顺序实施。It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein.

此外,术语“包括”和“具有”以及他们的任何变形,意图在于覆盖不排他的包含。例如,包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元,而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or inherent to these processes, methods, products, or apparatuses.

为了便于描述,在这里可以使用空间相对术语,如“在……之上”、“在……上方”、“在……上表面”、“上面的”等,用来描述如在图中所示的一个器件或特征与其他器件或特征的空间位置关系。应当理解的是,空间相对术语旨在包含除了器件在图中所描述的方位之外的在使用或操作中的不同方位。例如,如果附图中的器件被倒置,则描述为“在其他器件或构造上方”或“在其他器件或构造之上”的器件之后将被定位为“在其他器件或构造下方”或“在其他器件或构造之下”。因而,示例性术语“在……上方”可以包括“在……上方”和“在……下方”两种方位。该器件也可以其他不同方式定位,如旋转90度或处于其他方位,并且对这里所使用的空间相对描述作出相应解释。For ease of description, spatially relative terms, such as "above", "above", "on the upper surface of", "above", etc., may be used herein to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" may include both "above" and "below". The device may also be positioned in other different ways, such as rotated 90 degrees or in other orientations, and the spatially relative descriptions used herein are interpreted accordingly.

在上面详细的说明中,参考了附图,附图形成本文的一部分。在附图中,类似的符号典型地确定类似的部件,除非上下文以其他方式指明。在详细的说明书、附图及权利要求书中所描述的图示说明的实施方案不意味是限制性的。在不脱离本文所呈现的主题的精神或范围下,其他实施方案可以被使用,并且可以作其他改变。In the above detailed description, reference is made to the accompanying drawings, which form a part of this document. In the accompanying drawings, similar symbols typically identify similar components unless the context indicates otherwise. The illustrated embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be used, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein.

以上所述仅为本申请的优选实施例而已,并不用于限制本申请,对于本领域的技术人员来说,本申请可以有各种更改和变化。凡在本申请的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本申请的保护范围之内。The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims (10)

1. A method of controlling a semi-active suspension, the method comprising:
determining an external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model;
acquiring random disturbance information of a road surface and performance parameters of a semi-active suspension;
determining a fuzzy regulation strategy according to the performance parameters of the semi-active suspension and the random disturbance information of the road surface;
and determining the adjusted control parameters according to the fuzzy adjustment strategy, and adjusting the suspension dynamic deflection, the wheel dynamic load and the vehicle body acceleration according to the adjusted control parameters.
2. The method according to claim 1, wherein the pre-established variable damping vibration damper simulation model is input with different input currents and excitation speeds, and is output with the outer characteristic curve.
3. The method for controlling a semi-active suspension according to claim 1, wherein the road surface random disturbance information is an identification of a road surface unevenness coefficient.
4. The method of claim 1, wherein the pre-established fuzzy tuning strategy includes determining the scaling factor of the corresponding variable domain by the input variable bias and the input variable bias rate of change.
5. The method of claim 4, wherein the input variable bias and the input variable bias change rate include five first fuzzy sets, the first fuzzy sets respectively representing different fuzzy states, the first fuzzy sets including PB positive, PM median, PS positive small, ZE zero, NS negative small, NM negative medium, NB negative large; the expansion factors of the variable domain comprise five second fuzzy sets, the second fuzzy sets represent the opening and closing control trend of the electromagnetic valve, and the second fuzzy sets comprise ZE being closed, S being small, M being medium, B being large and K being open.
6. A control system for a semi-active suspension, the system comprising:
the first determining module is used for determining an external characteristic curve of the shock absorber according to a pre-established variable damping shock absorber simulation model;
the acquisition module is used for acquiring random disturbance information of the road surface and performance parameters of the semi-active suspension;
the second determining module is used for determining a fuzzy regulation strategy according to the performance parameters of the semi-active suspension and the random disturbance information of the road surface;
the adjusting module is used for determining the adjusted control parameters according to the fuzzy adjusting strategy and adjusting the suspension deflection, the wheel dynamic load and the vehicle body acceleration according to the adjusted control parameters.
7. The control system of a semi-active suspension as recited in claim 6 wherein said pre-established variable damping shock absorber simulation model is input for different input currents and excitation speeds and output as said outer characteristic.
8. The control system of a semi-active suspension of claim 6, wherein the road surface random disturbance information is an identification of a road surface unevenness coefficient.
9. The control system of a semi-active suspension of claim 6, wherein the pre-established fuzzy tuning strategy includes determining a telescoping factor for a corresponding variable domain by an input variable bias and an input variable bias rate of change.
10. The control system of a semi-active suspension of claim 9, wherein the input variable bias and the input variable bias rate of change include five first fuzzy sets, the first fuzzy sets representing different fuzzy states, respectively, the first fuzzy sets including PB positive large, PM median, PS positive small, ZE zero, NS negative small, NM negative medium, NB negative large; the expansion factors of the variable domain comprise five second fuzzy sets, the second fuzzy sets represent the opening and closing control trend of the electromagnetic valve, and the second fuzzy sets comprise ZE being closed, S being small, M being medium, B being large and K being open.
CN202310079638.8A 2023-02-07 2023-02-07 Semi-active suspension control method and system Active CN116080326B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310079638.8A CN116080326B (en) 2023-02-07 2023-02-07 Semi-active suspension control method and system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310079638.8A CN116080326B (en) 2023-02-07 2023-02-07 Semi-active suspension control method and system

Publications (2)

Publication Number Publication Date
CN116080326A true CN116080326A (en) 2023-05-09
CN116080326B CN116080326B (en) 2024-06-14

Family

ID=86208041

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310079638.8A Active CN116080326B (en) 2023-02-07 2023-02-07 Semi-active suspension control method and system

Country Status (1)

Country Link
CN (1) CN116080326B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116901639A (en) * 2023-07-03 2023-10-20 盐城工学院 Vibration reduction control method for active suspension of automobile

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5483450A (en) * 1993-04-28 1996-01-09 Siemens Automotive S.A. Apparatus for controlling a suspension system disposed between a wheel and the body of an automotive vehicle
CN103308327A (en) * 2012-03-07 2013-09-18 长春孔辉汽车科技有限公司 In-loop real-time simulation test system for suspension component
CN109927501A (en) * 2019-03-12 2019-06-25 辽宁科技大学 A kind of intelligent control method of Vehicle Semi-active Suspension System
CN112947087A (en) * 2021-02-03 2021-06-11 齐鲁工业大学 Semi-active suspension enhanced multi-fuzzy PID control system and method
CN114683795A (en) * 2022-03-31 2022-07-01 重庆长安汽车股份有限公司 Road surface self-adaptive semi-active suspension control method and system

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5483450A (en) * 1993-04-28 1996-01-09 Siemens Automotive S.A. Apparatus for controlling a suspension system disposed between a wheel and the body of an automotive vehicle
CN103308327A (en) * 2012-03-07 2013-09-18 长春孔辉汽车科技有限公司 In-loop real-time simulation test system for suspension component
CN109927501A (en) * 2019-03-12 2019-06-25 辽宁科技大学 A kind of intelligent control method of Vehicle Semi-active Suspension System
CN112947087A (en) * 2021-02-03 2021-06-11 齐鲁工业大学 Semi-active suspension enhanced multi-fuzzy PID control system and method
CN114683795A (en) * 2022-03-31 2022-07-01 重庆长安汽车股份有限公司 Road surface self-adaptive semi-active suspension control method and system

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116901639A (en) * 2023-07-03 2023-10-20 盐城工学院 Vibration reduction control method for active suspension of automobile

Also Published As

Publication number Publication date
CN116080326B (en) 2024-06-14

Similar Documents

Publication Publication Date Title
Turnip et al. Hybrid controller design based magneto-rheological damper lookup table for quarter car suspension
CN107825930B (en) An intelligent fuzzy hybrid shed semi-active control method for vehicle suspension system
CN111055650B (en) Magneto-rheological semi-active suspension particle swarm-time lag dependence H infinity robust control method
Mouleeswaran Design and development of PID controller-based active suspension system for automobiles
Kumar et al. Analytical and experimental studies on active suspension system of light passenger vehicle to improve ride comfort
Koulocheris et al. A comparison of optimal semi-active suspension systems regarding vehicle ride comfort
Chen et al. Probe into necessity of active suspension based on LQG control
CN116080326B (en) Semi-active suspension control method and system
CN110901326A (en) A control method of active suspension system with state constraints and dead zone input
Tang et al. A takagi-sugeno fuzzy model-based control strategy for variable stiffness and variable damping suspension
Sathishkumar et al. Reducing the seat vibration of vehicle by semi active force control technique
Ferhath et al. A review on various control strategies and algorithms in vehicle suspension systems
Najm et al. Mathematical modelling and PID controller implementation to control linear and nonlinear quarter car active suspension
CN112947087B (en) Semi-active suspension enhanced multiple fuzzy PID control system and method
Abdulhammed et al. Development of a new automotive active suspension system
Ismail et al. A control performance of linear model and the MacPherson model for active suspension system using composite nonlinear feedback
Shaqarin et al. A nonlinear quarter-car active suspension design based on feedback linearisation and H∞ control
Xia et al. Energy Flow Characteristics Analysis-Based Switching Control Strategy for Vehicle Suspension With Multifunction Electromagnetic Damper
CN111231595B (en) Semi-active suspension control method considering dynamic coupling of front axle and rear axle of automobile
Tang et al. Sliding Mode Control of Vehicle Semi-active Suspension System Based on Magnetorheological Damper
Díaz-Choque et al. Supervisor-Based Switching Strategy for Semi-Active Suspension Control
Sitompul et al. Enhancing comfort and handling in semi-active suspension systems with fuzzy controller
Dandavate et al. A Review on Controlling Methods for Active Suspension Systems
Desikan et al. Design for a semi-active preview suspension system using fuzzy-logic control and image processing techniques
Kannan et al. Discretization-Based Semi-Active Suspension Control Using Road Preview Data

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant